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At least 703 records · Page 39

Synoptic NO3 in Slate River Watershed, Colorado (2022)

The synoptic nitrate (NO3) dataset in the Slate River Watershed, Colorado consists of NO3 data collected at 19 locations three times during the summer of 2022. Stream samples were collected in early summer (early July), mid summer (late August), and late summer (late September). The samples include mainstem, tributary, and point source input water samples. These data were collected to evaluate spatiotemporal variability in stream NO3 during the summer, and evaluate anthropogenic controls on stream NO3 dynamics. This data package contains: (1) a csv of all NO3 samples and (2) a csv of locations for each sampling site. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATE↗

SPHERE Assembly and Operation Demonstration

The objective of the current scope was to complete single primary heat extraction and removal emulator (SPHERE) assembly and demonstrate the operation of the SPHERE facility. The initial testing consisted of vacuum operation of a sodium heat pipe. The temperature was measured at 10 evenly spaced points along the heat pipe. Additional exterior thermocouple measurements were also taken on the exterior of the heat pipe to confirm the similarity of thermowell temperatures to exterior heat pipe temperature measurements. The initial test was successfully completed and results measured at INL are consistent with the data from the manufacturer.

42 ENGINEERING↗

Thermal Spectrum Molten Salt-Fueled Reactor Reference Plant Model

This report details a fully coupled neutronics thermal hydraulics reference plant model for a thermal spectrum molten salt-fueled reactor. The Multiphysics model is developed on the Nuclear Regulatory Commission's Comprehensive Reactor Analysis Bundle available on the Idaho National Laboratory high-performance computer, which natively and seamlessly couples Griffin and Sam codes of the Multiphysics Object-Oriented Simulation Environment (MOOSE) based applications. Griffin provides the reactor physics capabilities, k-eigenvalue, delayed neutron precursor concentrations, and transient solutions for stationary and flowing fuels. Sam provides the solution of mass, momentum, and energy conservation equations of the whole system with a set of system components for one-dimensional single-phase flow. The neutronics feedback model relies primarily on fuel and moderator temperatures, fuel salt density, and delayed neutron precursors distributions. This report presents our results for the coupled steady state core and an unprotected loss of flow event. Although this model is prototypical regarding capabilities in the Comprehensive Reactor Analysis Bundle, its results are consistent with experimental data of the pump transient tests that were performed at zero power of the Molten Salt Reactor Experiment (MSRE).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Differential Scanning Calorimetry Calibration and Heat Capacity

The Differential Scanning Calorimeter(DSC) is used to find multiple properties ofmaterials such as heat capacity, melting points, crystallization, and more. Fermilabowns the NETZSCH DSC 404 F3 Pegasus to test novel material for a high poweredtargetry components. The DSC heats up to 1500 C, uses a platinum furnace, and Al 2 O 3 crucibles. In order for the DSC to produce consistent and correct data,calibration of the machine was necessary. Testing with the given calibration kit ofknown metals. Once calibrated, testing on novel materials for their specific heatcapacity ensues.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sequential Decision Making (SDM) for Mesh Refinement and Model Selection in Multiscale, Multi-Physics Applications

Intelligent automation and decision support are needed to enhance computational efficiency and robustness in multiscale and multi-physics problems, including materials science, manufacturing, and climate and weather modeling. Current scientific computing approaches for enabling decisions by scientists fail to explore the role of learning, reasoning, and probabilistic planning. Often these decisions are not performed in real-time during the computation but are made prior to the start of the computation, which must be interrupted in order to make changes to the prior choices. Such interruptions at different stages of the computation increase the total computing time and the need for a human expert to frequently monitor the results. State of art scientific computing methods consist of rule-based algorithms that cannot automatically adapt to a dynamically changing computing environment. The development of a Sequential Decision Making (SDM) framework will automate scientific computing by optimizing the policies for mesh refinement, time-stepping, model and algorithm selection, resource allocation, and pre and post-processing. Our agent SDM framework for scientific computing will consist of data-driven learning (Classifier), automated reasoning (contextual knowledge), and probabilistic planning (Reinforcement Learning). In this project, we focused on three problems to demonstrate our SDM framework on a set of ordinary and partial differential equations. Classification of Lorenz system regions using Feed-Forward Neural Networks examined learning in the SDM framework. On the other hand, reasoning and planning in the SDM framework were used in two problems: adaptive time-stepping for nonlinear ODEs using on-policy RL algorithms, and adaptive mesh refinement for 2-D PDEs using off-policy RL algorithms.

97 MATHEMATICS AND COMPUTING↗

Assessing Historical Extreme Weather Event Impacts

Understanding how past extreme weather events have affected a site is an integral part of site-level resilience planning. Energy and water resilience planning has been a key priority for the federal government for many years and agencies look to develop processes for identifying and addressing critical resilience gaps at their facilities and across their sites. The purpose of this information paper is to help inform how organizations could begin structuring a comprehensive process for recording the impacts of extreme weather events in order to facilitate climate vulnerability assessments, and thus, resilience planning. The paper highlights current limitations for developing event history assessments and suggests a framework for more consistently capturing key data points.

54 ENVIRONMENTAL SCIENCES↗

Assessing Historical Extreme Weather Event Impacts

Resilience planning, particularly energy and water resilience planning, has been a key priority for the federal government for many years, leading federal agencies to develop processes for identifying and addressing critical resilience gaps at their facilities and sites. Furthermore, recent federal policy is driving agencies to prioritize climate change impacts as a more central component of their resilience planning efforts. To achieve this, federal sites must understand their vulnerability to climate change, which involves identifying climate hazards projected to impact the site (known as exposure), as well as understanding the sensitivity (the degree to which a site, including its people and the things they value, could be harmed by that exposure), and adaptive capacity of the site (the degree to which the site could lessen bathe potential for harm by taking action to reduce exposure and sensitivity). To assess and understand sensitivity and adaptive capacity, it is important to first obtain a baseline and understand how a site has been impacted by past events, in addition to considering the potential for unprecedented impacts based on climate projections. This information paper highlights current limitations for developing event history assessments and suggests a framework for more consistently capturing key data points. The purpose of this paper is to help inform how organizations could begin structuring a comprehensive process for recording the impacts of extreme weather events in order to facilitate climate vulnerability assessments, and thus, resilience planning.

54 ENVIRONMENTAL SCIENCES↗

Quarterly Research Performance Progress Report

The goal of this project is to develop a high temperature, high-pressure well integrity evaluation device that can operate in enhanced geothermal system (EGS) boreholes without active cooling or substantial mitigation of borehole conditions. The product must provide consistent high resolution data regarding the efficacy of wellbore casing and cement for long-term operation. This project aims to deliver a ruggedized tool that can withstand a corrosive geothermal environment with pressure ranges up to 15,000 psi and temperatures up to 250°C for a 24-hour operating period.

15 GEOTHERMAL ENERGY↗

Estimating vehicle fuel economy from overhead camera imagery and application for traffic control

In this work, we explore the ability to estimate vehicle fuel consumption using imagery from overhead fisheye lens cameras deployed as traffic sensors. We utilize this information to simulate vision-based control of a traffic intersection, with a goal of improving fuel economy with minimal impact to mobility. We introduce the ORNL Overhead Vehicle Dataset (OOVD), consisting of a data set of paired, labeled vehicle images from a ground-based camera and an overhead fisheye lens traffic camera. The data set includes segmentation masks based on Gaussian mixture models for vehicle detection. We show the dataset utility through three applications: the estimate of fuel consumption based on segmentation bounding boxes, vehicle discrimination for those vehicles with largest bounding boxes, and a fine-grained classification on a limited number of vehicle makes and models using a pre-trained set of convolutional neural network models. We compare these results with estimates based on a large open-source data set based on web-scraped imagery. Finally, we show the utility of the approach using reinforcement learning in a traffic simulator using the open source Simulation of Urban Mobility (SUMO) package. Our results show the feasibility of the approach for controlling traffic lights for better fuel efficiency based solely on visual vehicle estimates from commercial, fisheye lens cameras.

Karnowski, Thomas↗

EVT 16s Data and Large Supplementary Files

Soil microorganisms often interact to carry out decomposition of complex organic carbon and nitrogen compounds, such as chitin, but the high diversity and complexity of the soil microbiome and habitat has posed a challenge to elucidating such interactions between soil microorganisms. Here, we seek to address this challenge through analysis of a model soil consortium (MSC-2) of eight soil bacterial species. Our aim was to elucidate specific roles of the member species during chitin metabolism. Samples were collected from MSC-2 incubated in chitin-enriched soil over three months. Multi-omics was used to understand how the community composition, transcripts, proteins and chitin decomposition shifted over time. The data clearly and consistently revealed a temporal shift during chitin decomposition with defined contributions by individual species. A Streptomyces genus member (sp001905665) was a key player in early steps of chitin decomposition, with other MSC-2 members being central in carrying out later steps. These results illustrate how multi-omics applied to a defined consortium untangles interactions between soil microorganisms.

McClure, Ryan [Pacific Northwest National Laborato↗

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗

Role of Simple Spatial Gradient in Reinforcing the Accuracy of Temperature Determination of HED Plasma via Spectral Line-Area Ratios

We report on the simulation of temperature gradients in tamped NaFMgO target-foil plasma, heated and backlit by z-pinch dynamic hohlraum radiation. Our approach compares the spectroscopic output of a collisional-radiative model (prismspect) with soft X-ray absorption spectra collected on Sandia National Laboratories’ (SNL) Z Pulsed Power Facility. The pattern of minimum χ2 is seen to agree with an efficient, three-parameter model. Results show that a negligible gradient in electron temperature Te is consistent with experimental data, justifying the assumptions of previous work. The predicted sensitivity of line spectra to the gradient-aligned profile of Te is documented for each spectral feature, so that the line-area ratio between a pair of spectral features may be assessed as a proxy for the existence and quantification of such gradients.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Some Aspects of the Liquid Water Thermodynamic Behavior: From The Stable to the Deep Supercooled Regime

Liquid water is considered to be a peculiar example of glass forming materials because of the possibility of giving rise to amorphous phases with different densities and of the thermodynamic anomalies that characterize its supercooled liquid phase. In the present work, literature data on the density of bulk liquid water are analyzed in a wide temperature-pressure range, also including the glass phases. A careful data analysis, which was performed on different density isobars, made in terms of thermodynamic response functions, like the thermal expansion αP and the specific heat differences C P -C V , proves, exclusively from the experimental data, the thermodynamic consistence of the liquid-liquid transition hypothesis. The study confirms that supercooled bulk water is a mixture of two liquid “phases”, namely the high density (HDL) and the low density (LDL) liquids that characterize different regions of the water phase diagram. Furthermore, the C P -C V isobars behaviors clearly support the existence of both a liquid–liquid transition and of a liquid–liquid critical point.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of Exported Plasmodium falciparum Proteins That Bind to the Erythrocyte Cytoskeleton

Plasmodium proteins are exported to the erythrocyte cytoplasm to create an environment that supports parasite replication. Although hundreds of proteins are predicted to be exported through Plasmodium export element (PEXEL)-dependent and -independent mechanisms, the functions of exported proteins are largely uncharacterized. In this study, we used a biochemical screening approach to identify putative exported P. falciparum proteins that bound to inside-out vesicles prepared from erythrocytes. Out of 69 P. falciparum PEXEL-motif proteins tested, 18 bound to inside-out vesicles (IOVs) in two or more independent assays. Using co-affinity purifications followed by mass spectrometry, pairwise co-purification experiments, and the split-luciferase assay, we identified 31 putative protein–protein interactions between erythrocyte cytoskeletal proteins and predicted exported P. falciparum proteins. We further showed that PF3D7_1401600 binds to the spectrin-binding domain of erythrocyte ankyrin via its MESA erythrocyte cytoskeleton binding (MEC) motif and to the N-terminal domains of ankyrin and 4.1R through a fragment that required an intact Plasmodium helical interspersed sub-telomeric (PHIST) domain. Introduction of PF3D7_1401600 into erythrocyte ghosts increased retention in the microsphiltration assay, consistent with previous data that reported a reduction of rigidity in red blood cells infected with PF3D7_1401600-deficient parasites.

59 BASIC BIOLOGICAL SCIENCES↗

The Population of H ii Regions in NGC 7020

The galaxy NGC 7020 displays an exotic hexagonal ringlike central structure with conspicuous ansae located at two opposite vertices and a tenuous external ring populated by H ii regions. Inside and around the hexagonal structure, Hα emission is also present at the inner disk. To characterize the population of the H ii regions, as well as their ionizing clusters, we imaged NGC 7020 with narrowband Hα and nearby continuum filters attached to GMOS-S installed on the Gemini South telescope. We found 202 H ii regions or complexes of H ii regions evenly distributed between the outer ring and the central disk The nucleus and ansae also present Hα emission. The equivalent width of the Hα line (W {sub Hα}) is systematically greater at the regions of the outer ring relative to those of the inner disk. We discuss the influence of the metallicity gradient of the disk and the upper limit of the masses of the initial mass function on W {sub Hα}, and we conclude that the data are still consistent with the occurrence of a younger burst of H ii region formation in the outer ring. The central regions present more massive clusters, M ≥ 10{sup 6} M {sub ⊙}, than those of the outer ring (M ≤ 10{sup 6} M {sub ⊙}). Three clusters within 5″ of the nucleus present masses higher than 10{sup 8} M {sub ⊙}. The presence of diffuse Hα emission in the inner 5″ suggests gas flows in the nuclear region.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Impact of Hypernova νp-process Nucleosynthesis on the Galactic Chemical Evolution of Mo and Ru

We calculate the Galactic Chemical Evolution of Mo and Ru by taking into account the contribution from νp-process nucleosynthesis. We estimate yields of p-nuclei such as 92,94 Mo and 96,98 Ru through the νp-process in various supernova progenitors based upon recent models. In particular, the νp-process in energetic hypernovae produces a large amount of p-nuclei compared to the yield in ordinary core-collapse SNe. Because of this, the abundances of 92,94 Mo and 96,98 Ru in the Galaxy are significantly enhanced at [Fe/H] = 0 by the νp-process. We find that the νp-process in hypernovae is the main contributor to the elemental abundance of 92 Mo at low metallicity [Fe/H] < −2. Our theoretical prediction of the elemental abundances in metal-poor stars becomes more consistent with observational data when the νp-process in hypernovae is taken into account.

79 ASTRONOMY AND ASTROPHYSICS↗

Properties of the Prompt Optical Counterpart Arising from the Cooling of Electrons in Gamma-Ray Bursts

This work extends a contemporaneous effort to study the properties of the lower-energy counterpart synchrotron emission produced by the cooling of relativistic gamma-ray burst (GRB) electrons through radiation (synchrotron and self-Compton) emission and adiabatic losses. We derive the major characteristics (pulse duration, lag time after burst, and brightness relative to the burst) of the prompt optical counterpart (POC) occurring during or after the GRB. Depending on the magnetic field lifetime, duration of electron injection, and electron transit time Δt o from hard X-ray (GRB) to optical-emitting energies, a POC may appear during the GRB pulse (of duration δt γ ) or after (delayed OC). The signature of counterparts arising from the cooling of GRB electrons is that POC pulses (Δto < δtγ) last as long as the corresponding GRB pulse (δt o ≃ δt γ ), while delayed OC pulses (Δt o > δt γ ) last as long as the transit time (δt o ≃ Δt o ). If OC variability can be measured, then another signature for this OC mechanism is that the GRB variability is passed on to POCs but not to delayed OCs. Within the GRB electron cooling model for counterparts, POCs should be on average dimmer than delayed ones (consistent with the data), and harder GRB low-energy slopes β LE should be associated more often with the dimmer POCs. The latter sets an observational bias against detecting POCs from (the cooling of electrons in) GRBs with a hard slope β LE , making it more likely that the detected POCs of such bursts arise from another mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling Dust Production, Growth, and Destruction in Reionization-era Galaxies with the CROC Simulations: Methods and Parameter Exploration

We introduce a model for the explicit evolution of interstellar dust in a cosmological galaxy formation simulation. We post-process a simulation from the Cosmic Reionization on Computers project, integrating an ordinary differential equation for the evolution of the dust-to-gas ratio along pathlines in the simulation sampled with a tracer particle technique. This model incorporates the effects of dust grain production in asymptotic giant branch star winds and supernovae, grain growth due to the accretion of heavy elements from the gas phase of the interstellar medium, and grain destruction due to thermal sputtering in the high-temperature gas of supernova remnants due to thermal sputtering. A main conclusion of our analysis is the importance of a carefully chosen dust destruction model, for which different reasonable parameterizations can predict very different values at the ∼100 pc resolution of the interstellar medium (ISM) in our simulations. We run this dust model on the single most massive galaxy in a 10 h$^{−1}$ comoving megaparsec box, which attains a stellar mass of ∼2 × 10$^{9}$ M $_{⊙}$ by z = 5. We find that the model is capable of reproducing dust masses and dust-sensitive observable quantities broadly consistent with existing data from high-redshift galaxies. The total dust mass in the simulated galaxy is somewhat sensitive to parameter choices for the dust model, especially the timescale for grain growth due to accretion in the ISM. Consequently, observable quantity observations that can constrain galaxy dust masses at these epochs are potentially useful for placing constraints on dust physics.

79 ASTRONOMY AND ASTROPHYSICS↗